CN115496015A - Hydrodynamic analysis decision method based on flow gradient change - Google Patents

Hydrodynamic analysis decision method based on flow gradient change Download PDF

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CN115496015A
CN115496015A CN202211442583.4A CN202211442583A CN115496015A CN 115496015 A CN115496015 A CN 115496015A CN 202211442583 A CN202211442583 A CN 202211442583A CN 115496015 A CN115496015 A CN 115496015A
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flow
water
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CN115496015B (en
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刘国珍
卢陈
张琴凤
袁菲
吴尧
佟晓蕾
杨裕桂
温舒茵
陈娟
黄鹏飞
王海俊
黄淞宣
林平
高时友
吴天胜
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Pearl River Hydraulic Research Institute of PRWRC
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    • G06F30/20Design optimisation, verification or simulation
    • G06F30/28Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
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    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
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    • G06COMPUTING; CALCULATING OR COUNTING
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    • G06V20/46Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames
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    • G06COMPUTING; CALCULATING OR COUNTING
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Abstract

The invention relates to the technical field of hydrodynamic analysis decision, in particular to a hydrodynamic analysis decision method based on flow gradient change. The method comprises the following steps: acquiring hydrological historical data, analyzing and generating a moving bed model; acquiring a real-time river channel water flow image and screening to obtain a clear river channel water flow frame image sequence; calculating the clear river water flow frame image sequence to generate a river water surface flow velocity region distribution map; analyzing hydrological real-time basic detection data and a river water surface flow velocity area distribution map to generate a river water flow real-time model; performing deduction calculation and analysis according to the moving bed model and the real-time river flow model to generate a hydrodynamic model for predicting future river bed evolution model and flow gradient change; and adding obstacles into the hydrodynamic model for flow gradient change and the model for predicting future riverbed evolution to carry out deduction, and generating a model for predicting the future riverbed evolution of interference. The invention can improve the decision efficiency.

Description

Hydrodynamic analysis decision method based on flow gradient change
Technical Field
The invention relates to the technical field of hydrodynamic analysis decision, in particular to a hydrodynamic analysis decision method based on flow gradient change.
Background
Along with the continuous deepening of urbanization, the water areas in regions such as river channels or river mouths of sea and the like are simultaneously influenced by runoff and tide, because the water areas involved in engineering are wide, the dynamic characteristics of different regions are greatly different, the contribution of each dynamic subarea is different corresponding to the functions of flood discharge, tide collection, sand discharge and the like, in order to control the influence of engineering on flood discharge and tide collection, the overall arrangement of the water-involved engineering is optimized, firstly, the dynamic subareas must be determined, the consequences of damage to building facilities, deterioration of ecological environment and the like caused by the influence of runoff and tide and flood disaster are improved, casualties and economic losses are caused, a series of other disasters are also caused, the hydrological hydrodynamic process of the process is deduced by simulating a future prediction change model of a riverbed, the dynamic visual analysis on the runoff, tide and flood process can be realized, and the prediction and the capability of coping with flood disaster can be improved, the method can greatly reduce flood disaster loss, improve the prediction and coping ability of runoff and tide, greatly improve the efficiency of the construction process, reduce the loss of the runoff and the tide to a construction water area, the hydrodynamic model with flow gradient change is a hydrokinetic interference process for predicting and interfering the future river evolution model to carry out the deduction process by the tidal current average flow of a section of a river channel or a sea estuary and the flood discharge ability is usually reflected by the tidal current average flow of the section, so that the dynamic visual analysis can be carried out on the construction scheme, the engineering construction address and the time of the river channel or the sea estuary and the like, the feasibility of engineering projects is improved, the construction mode is deduced, and the influence of the engineering on the river channel or the sea estuary and the like is reduced.
The forecasting interference future river channel evolution model can improve the efficiency of engineering decision and implementation and save time cost. The existing hydrohydrodynamic process numerical simulation method can accurately simulate the flood evolution process, but cannot deduce and make decisions on the interfered hydrohydrodynamic, the hydraulic information prediction capability of flood needs to be improved, and most numerical simulation methods cannot realize the simulation of large-scale urban areas and large-scale watersheds in the aspect of large-scale area simulation; in the aspect of fine terrain simulation, the problem of low simulation calculation efficiency can also exist.
Disclosure of Invention
The present invention provides a hydrodynamic analysis decision method based on flow gradient change to solve at least one of the above technical problems.
In order to achieve the above object, the present invention provides a hydrodynamic analysis decision method based on flow gradient change, comprising the following steps:
step S1: acquiring hydrological historical data, analyzing the hydrological historical data and generating a moving bed model;
step S2: acquiring a real-time river water flow image, and analyzing and screening the real-time river water flow image to obtain a clear river water flow framing image sequence;
and step S3: carrying out a plurality of fixed point sampling calculations on the clear river water flow frame image sequence to generate a river water flow velocity region distribution map;
and step S4: acquiring hydrological real-time basic detection data, analyzing the hydrological real-time basic detection data and a river water surface flow velocity area distribution diagram, and generating a river water flow real-time model;
step S5: performing deduction calculation according to the moving bed model and the river flow real-time model to generate a model for predicting future river bed evolution;
step S6: carrying out partition analysis on the river channel hydrodynamic force according to the moving bed model and the river channel water flow change model to generate a hydrodynamic force model with flow gradient change;
step S7: adding obstacles into a hydrodynamic model of flow gradient change and a riverbed future prediction change model for deduction to generate a prediction interference future riverway evolution model;
step S8: and generating an optimal construction and construction decision according to the prediction interference future river channel evolution model.
The hydrologic history data of the embodiment includes: the river course rivers sand content change data, the river course impact plains change data of the past year and island change data are piled up to the river course slow current of the past year, etc., carry out the analysis to hydrology historical data and obtain the moving bed model, be favorable to the audio-visual historical evolution process that obtains the riverbed, be favorable to making the analysis to the riverbed future evolution and provide data support, can obtain the riverbed density distribution and provide technical data to bridge pedestal, the construction of river course construction projects such as water conservancy dam and edge river dykes and dams is provided technical data, carry out the analysis to river course rivers image, the velocity of flow that is favorable to the analysis to obtain river course surface rivers is analyzed river surface velocity of flow and river basin undercurrent, thereby establish more accurate river course rivers real-time model, hydrology real-time basis detection data include: the method comprises the steps of generating a riverway water flow real-time model according to hydrological real-time basis detection data and a riverway water surface flow velocity region, considering influence factors of riverway water flow from multiple aspects so as to enable the riverway water flow real-time model to be closer to the actual situation, providing more accurate and efficient data for subsequent analysis, predicting future riverway evolution model to be used for deducing riverway future under natural conditions of the riverway to be beneficial to development and management of the riverway, preventing flood and reducing disasters, reducing life and property loss, providing data support for predicting interference future riverway evolution model, predicting the interference future riverway evolution model to be used for judging indexes of hydrodynamic subareas by researching riverway water flow gradient changes, analyzing tidal power of sections of regions such as the riverway or a sea river mouth and the like, wherein the tidal power of the sections is generally reflected by the average flow of flood tide of the sections, the flood discharge capacity is generally reflected by the average flow of tide of the sections, and predicting the interference future evolution model of the interference riverway to be used for the evolution process under various interference conditions, and is beneficial to carry out deduction influence of the riverway on the riverway influence of construction, flood discharge capacity and the ecological flood discharge capacity.
In one embodiment of the present description, the hydrologic history data includes: the method comprises the following steps of 1, acquiring historical water level height and flow rate data, historical river water flow sand content change data, historical river impact plateau change data and historical river slow flow accumulation island change data, wherein the step S1 comprises the following steps:
acquiring hydrological historical data;
summarizing and analyzing the change data of the river channel impact plains and the change data of the river channel slow-flow accumulation islands in the past years to obtain the current river channel sand accumulation distribution area and distribution density;
the current river channel sand accumulation distribution area and distribution density are speculatively analyzed according to the water level height and flow speed data of the past year to generate a riverbed sediment accumulation change model;
calculating and analyzing the water level height and flow rate data in the past year to obtain a relation function of the water level height and the flow rate, and performing summary modeling on the relation function of the water level height and the flow rate and the river water sand content change data to generate a river water change model;
and aggregating the riverbed sediment accumulation change model and the riverway water flow change model to generate a moving bed model.
In the embodiment, by summarizing and analyzing the change data of the river channel impact plains in the past and the change data of the river channel slow-flow accumulation islands in the past, the accumulation distribution area and the distribution density of sand and soil in the river channel can be visually obtained, in other words, a distribution map of the sediment thickness of the river channel and a distribution map along with historical changes can be obtained, the structure and the density of a river bed can be favorably known, and the data support is improved for river channel engineering such as bridges and the like; the current river channel sand and soil accumulation distribution area and distribution density are speculatively analyzed according to the historical water level height and flow rate data to obtain a riverbed sediment accumulation change model, and the historical change of the riverbed is favorably known through analyzing the historical water level height and flow rate data; the method comprises the steps of obtaining a relation function of water level height and flow speed by calculating and analyzing data of water level height and flow speed in the past year, carrying out summary modeling on the relation function of water level height and flow speed and river water sand content change data to obtain a river water flow change model, obtaining the relation function of water level height and flow speed by deduction calculation, and facilitating the conjecture of future changes of the river; the riverbed sediment accumulation change model and the riverway water flow change model are aggregated to obtain a moving bed model, and the two models are combined to facilitate visual checking of the whole historical transition process of the riverway and provide data support for raising and constructing the riverway.
In an embodiment of the present specification, the calculation and analysis of the water level height and the flow rate data over the years are performed to obtain a relation function between the water level height and the flow rate, where a calculation formula of the relation function between the water level height and the flow rate, which is obtained by calculating the water level height and the flow rate data over the years, includes the following formula:
water level height variation function:
Figure 100002_DEST_PATH_IMAGE001
wherein, the first and the second end of the pipe are connected with each other,
Figure 95010DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 100002_DEST_PATH_IMAGE003
as represented by the time period variable,
Figure 798524DEST_PATH_IMAGE004
expressed as a variable over a period of time
Figure 484720DEST_PATH_IMAGE003
One of the time period variables in (a),
Figure 100002_DEST_PATH_IMAGE005
expressed as a certain period of time
Figure 222869DEST_PATH_IMAGE004
The corresponding upstream water flow rate is set,
Figure 601898DEST_PATH_IMAGE006
expressed as a certain period of time
Figure 527128DEST_PATH_IMAGE004
The corresponding rainfall capacity is set as the corresponding rainfall capacity,
Figure 100002_DEST_PATH_IMAGE007
expressed as a certain period of time
Figure 282595DEST_PATH_IMAGE004
The corresponding industrial and civil discharge water flow,
Figure 344092DEST_PATH_IMAGE008
expressed as a certain period of time
Figure 894022DEST_PATH_IMAGE004
The average temperature of the corresponding temperature of the sample,
Figure 100002_DEST_PATH_IMAGE009
expressed as a certain period of time
Figure 837707DEST_PATH_IMAGE004
Correspondingly observing the total river water evaporation capacity of the river channel,
Figure 865706DEST_PATH_IMAGE010
expressed as a certain period of time
Figure 312868DEST_PATH_IMAGE004
The corresponding total water consumption of the local industry and agriculture to the river channel,
Figure 100002_DEST_PATH_IMAGE011
an offset expressed as a function;
water flow velocity variation function:
Figure 33699DEST_PATH_IMAGE012
wherein the content of the first and second substances,
Figure 100002_DEST_PATH_IMAGE013
expressed as a function of the change in the flow rate of the water,
Figure 199101DEST_PATH_IMAGE014
expressed as the length of the river channel to be observed,
Figure DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed
Figure 30791DEST_PATH_IMAGE014
The length of one section of the river channel in the river channel,
Figure 598038DEST_PATH_IMAGE016
expressed as a certain length of the river
Figure 958613DEST_PATH_IMAGE015
The width of the corresponding downstream river channel,
Figure DEST_PATH_IMAGE017
expressed as a certain length of the river
Figure 876890DEST_PATH_IMAGE015
The width of the corresponding upstream river channel,
Figure 246691DEST_PATH_IMAGE018
expressed as a certain length of the river
Figure 402866DEST_PATH_IMAGE015
The average depth of the corresponding river bed,
Figure 465500DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure DEST_PATH_IMAGE019
an offset expressed as a function;
the relation function calculation formula of the water level height and the flow velocity is as follows:
Figure 339915DEST_PATH_IMAGE020
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE021
expressed as a function of water level height and flow rate,
Figure 44566DEST_PATH_IMAGE022
indicated as a start time for starting recording of the respective items of data,
Figure DEST_PATH_IMAGE023
indicated as the end of the last recorded item of dataIn which
Figure 320827DEST_PATH_IMAGE024
Figure 554362DEST_PATH_IMAGE003
As represented by the time period variable,
Figure DEST_PATH_IMAGE025
indicated as the initial observation position upstream of the river,
Figure 916073DEST_PATH_IMAGE026
expressed as the observation position of the downstream end of the river channel, wherein
Figure DEST_PATH_IMAGE027
Figure 158836DEST_PATH_IMAGE014
Expressed as the length of the river channel to be observed,
Figure 289603DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 694039DEST_PATH_IMAGE028
expressed as a function of the change in the flow rate of the water,
Figure DEST_PATH_IMAGE029
respectively, are represented as constants of a function,
Figure 543047DEST_PATH_IMAGE030
expressed as an offset of a function.
The water level height variation function of the embodiment is used for calculating the variation relation of the water level height of the river channel, and measuring data of the river channel in a time period is utilized
Figure 58342DEST_PATH_IMAGE003
Performing a calculation at a current time period
Figure 43615DEST_PATH_IMAGE003
Regarding the variation function of the water level height, the variation function of the river water level height is calculated through all-directional data, and the influence factor of the water level height has the upstream water flow
Figure DEST_PATH_IMAGE031
Rainfall and rainfall
Figure 884532DEST_PATH_IMAGE032
Industrial and civil drainage flow
Figure DEST_PATH_IMAGE033
Average temperature of
Figure 220836DEST_PATH_IMAGE034
Total river water evaporation
Figure DEST_PATH_IMAGE035
The total water consumption of the river channel by local industry and agriculture
Figure 805401DEST_PATH_IMAGE036
All are factors which have certain influence on the change of the river water level height, and the influence factors of the river channel with comprehensive consideration rate enable the calculated water level height change function to more accurately correspond to the current time period
Figure 910760DEST_PATH_IMAGE003
The water level height variation relation is used for predicting the future water level height; using exponential functions
Figure DEST_PATH_IMAGE037
Real-time data having a direct relation to the height of the river water level is used for enhancing the function;
the water flow velocity variation function is used for calculating the variation relation of the water flow velocity of the river channel isolated water area and is utilized at the river section needing to be detected
Figure 656999DEST_PATH_IMAGE014
The flow velocity of the river reach is calculated by all data, and the flow velocity of the river reach is calculated by all-directional dataThe variation forming function has the influence factor on the water flow velocity of the downstream river channel width
Figure 215019DEST_PATH_IMAGE038
Upstream river width
Figure DEST_PATH_IMAGE039
Average depth of riverbed
Figure 337696DEST_PATH_IMAGE040
And water level height variation function
Figure 297562DEST_PATH_IMAGE002
The factors have certain influence on the change of the river course water flow velocity, and the influence factors of the river course water flow velocity are comprehensively considered, so that the calculation of the water flow velocity change function and the accuracy have calculation basis on the preset future river course water flow velocity;
the relation function calculation formula of the water level height and the flow velocity is used for calculating the relation formula of the water level height and the flow velocity of water flow, and the water level height change function is utilized
Figure 214702DEST_PATH_IMAGE002
As a function of the velocity of water flow
Figure 525598DEST_PATH_IMAGE013
Form a relation function
Figure DEST_PATH_IMAGE041
For obtaining a function of water level and flow rate, using a double integral pair
Figure 186386DEST_PATH_IMAGE042
The function is calculated, which is beneficial to knowing the relation of the function.
In one embodiment of the present description, step S2 includes the steps of:
acquiring a real-time river water flow image;
framing the real-time river channel water flow image to obtain a river channel water flow framing image sequence, and performing convolution on the river channel water flow framing image sequence to obtain a clear river channel water flow framing image set;
and counting the clear river water flow framing image set according to the river water flow framing image sequence to obtain the clear river water flow framing image sequence.
In the embodiment, the real-time river channel water flow image is framed to obtain the river channel water flow framed image, which is used for identifying river channel water flow ripples, calculating the water flow velocity of the river channel water surface and providing data support for subsequently establishing a river channel water flow velocity model; and counting the clear river water flow framing image set according to the river water flow framing image sequence, so as to more clearly extract a river water flow ripple image for subsequent calculation.
In one embodiment of the present description, step S3 includes the steps of:
step S51: extracting water surface ripple characteristic points from the clear river water flow framing images in the clear river water flow framing image sequence to obtain a water surface ripple characteristic point set of each clear river water flow framing image;
step S52: matching a water surface ripple characteristic point set of a current clear river flow framing image with a water surface ripple characteristic point set of a next clear river flow framing image in the clear river flow framing image sequence to obtain a current matching characteristic point set;
step S53: matching the clear river water flow frame image with the next clear river water flow frame image in sequence according to the method in the step S52 to obtain a full-image matching feature point set, and calculating the relative position of the full-image matching feature point set in the clear river water flow frame image to generate a matching feature point motion data set;
step S54: and labeling the clear river water flow frame images according to the matched feature point motion data set and the full-image matched feature point set to generate a river water flow velocity region distribution map.
This embodiment draws surface of water ripple characteristic point to the clear river course rivers framing image in the clear river course rivers framing image sequence, be favorable to calculating that same ripple is used for calculating single point river course rivers surface of water velocity of flow in the position of other images along with the time change, obtain river course rivers surface of water velocity of flow according to the multiple spot computing mode, calculate according to the multiple spot and obtain rivers surface of water velocity condition and generate river course surface of water velocity regional distribution diagram, the follow-up research river course rivers velocity of flow of being convenient for provides data support, be favorable to setting up and correcting the operation to river course rivers velocity of flow model.
In an embodiment of the present specification, step S4 specifically is:
acquiring hydrological real-time basic inspection data, wherein the hydrological basic hydrological data comprise riverbed depth, riverbed length, rainfall and flow data;
generating average flow speed data according to precipitation and rainfall and the flow data;
calculating the average flow velocity data according to the depth and the length of the riverbed by a riverbed flow calculation formula to generate a riverbed flow velocity data distribution set;
and correcting and adjusting the river bed flow velocity data distribution set according to the river course water flow surface velocity area distribution map to generate a river course water flow real-time model.
This embodiment generates riverbed velocity of flow data distribution set through the calculation to be used for revising the adjustment to riverbed velocity of flow data distribution set to riverway water face velocity of flow regional distribution diagram, has generated the real-time model of riverway rivers, and this model plays the directly perceived display effect of model to studying riverway historical rivers change and predicting future riverway rivers change, and the popularization work and the study of being convenient for to know riverway rivers change play the auxiliary role.
In an embodiment of the present specification, the riverbed flow calculation formula is specifically:
Figure DEST_PATH_IMAGE043
wherein the content of the first and second substances,
Figure 759DEST_PATH_IMAGE044
expressed as the flow of the river bed,
Figure 366098DEST_PATH_IMAGE003
as represented by the time period variable,
Figure 898711DEST_PATH_IMAGE004
expressed as a variable over a period of time
Figure 97611DEST_PATH_IMAGE003
One of the time period variables in (a),
Figure DEST_PATH_IMAGE045
expressed as a certain period of time
Figure 32069DEST_PATH_IMAGE004
The corresponding water flow velocity change function,
Figure 291012DEST_PATH_IMAGE040
expressed as the average bed depth of the river to be observed,
Figure 310921DEST_PATH_IMAGE038
expressed as the downstream channel width of the channel to be observed,
Figure 313512DEST_PATH_IMAGE039
expressed as the upstream channel width of the channel to be observed,
Figure 102476DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 532320DEST_PATH_IMAGE014
expressed as the length of the river channel to be observed,
Figure 773946DEST_PATH_IMAGE046
expressed as an offset of a function.
The riverbed flow calculation formula is used for calculating the river flow, and measuring data of the river within a period of time is utilized
Figure 314649DEST_PATH_IMAGE003
Performing a calculation at a current time period
Figure 223699DEST_PATH_IMAGE003
Regarding the water flow, the river water flow is calculated through omnibearing data, and the influence factor on the water flow has a water flow velocity change function
Figure 824444DEST_PATH_IMAGE013
Average depth of riverbed
Figure 553366DEST_PATH_IMAGE040
Downstream river width
Figure 897760DEST_PATH_IMAGE038
Upstream river width
Figure 661316DEST_PATH_IMAGE039
Water level height variation function
Figure 167384DEST_PATH_IMAGE002
And the length of the river channel to be observed
Figure 649181DEST_PATH_IMAGE014
All are factors which have certain influence on the change of the river flow, and the influence factors of the river channel with comprehensive consideration rate enable the calculated river bed flow to correspond to the current time period more accurately
Figure 797266DEST_PATH_IMAGE003
The water level height change relation is used for estimating the future river channel water flow and river channel tide receiving and flood discharging, and navigation and ecological functions of the river channel are ensured.
In an embodiment of the present specification, step S5 specifically includes:
generating real-time river channel change data through a river channel water flow real-time model and a river channel water flow self-change function calculation formula;
modifying and adjusting the moving bed model according to the real-time change data of the river channel to generate a model for predicting the future river bed evolution;
the riverway water flow self-changing function calculation formula is specifically as follows:
Figure DEST_PATH_IMAGE047
wherein the content of the first and second substances,
Figure 415329DEST_PATH_IMAGE048
the river course water flow is self-changing function,
Figure 623456DEST_PATH_IMAGE023
indicated as the end time of the last recording of each item of data,
Figure 61391DEST_PATH_IMAGE014
expressed as the length of the river channel to be observed,
Figure 747587DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed
Figure 485736DEST_PATH_IMAGE014
The length of one section of the river channel in the river channel,
Figure 333606DEST_PATH_IMAGE021
expressed as a function of water level height and flow rate,
Figure DEST_PATH_IMAGE049
expressed as the sand content of the river channel per unit time,
Figure 789995DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 279882DEST_PATH_IMAGE013
expressed as a function of the change in the flow rate of the water,
Figure 872538DEST_PATH_IMAGE044
expressed as the flow of the river bed,
Figure 422468DEST_PATH_IMAGE050
expressed as an offset of a function.
The river course water flow self-changing function calculation formula is used for calculating the river course water flow self-changing condition, and measuring data of the river course in a time period is utilized
Figure 834995DEST_PATH_IMAGE003
Performing a calculation at a current time period
Figure 862993DEST_PATH_IMAGE003
The water flow self-change is calculated through omnibearing data, and the influence factor of the water flow self-change has a relation function of water level height and flow velocity
Figure 310155DEST_PATH_IMAGE021
Unit time river sand content
Figure 765407DEST_PATH_IMAGE049
Water level height variation function
Figure 930810DEST_PATH_IMAGE002
Figure 496920DEST_PATH_IMAGE028
Water flow velocity variation function and riverbed flow
Figure 798588DEST_PATH_IMAGE044
The calculation and the conjecture of the future change direction and distance of the river water flow are carried out, and the influence factor of the river channel with the overall consideration rate enables the calculation of the self-change of the river channel to be more accurate and correspond to the current time period
Figure 690321DEST_PATH_IMAGE003
The relationship of the water level height change is used for increasing the influence of the relationship quantity of historical data of each section of river channel on the self-change of the river channel through accumulation, derivation is carried out on the relationship quantity to obtain the relationship slope and the area of the function, the relationship slope and the area are used for conjecturing the self-change direction and the trend of the river channel, the establishment of a model for predicting the future river bed evolution is facilitated, the conjecture of the future river bed change is carried out, and the direction is provided for the future development and construction of the river channel.
In an embodiment of the present specification, step S6 specifically is:
carrying out partition analysis on river channel hydrodynamic force according to hydrological historical data, a moving bed model and a river channel water flow change model to generate average rising tide flow data, average falling tide flow data and corresponding flood discharge and tide receiving position information;
and generating a sensitive river reach subarea by unit width flow calculation according to the average rising flow data, the average falling flow data and the corresponding flood discharge and tide receiving position information, wherein the sensitive river reach subarea comprises general sensitive water area information, more sensitive water area information and sensitive water area information, and a hydrodynamic model with flow gradient change is generated.
In this embodiment, river hydrodynamic force is subjected to partition analysis according to hydrological historical data, a moving bed model and a river water flow change model to generate average tidal rise flow data, average tidal fall flow data and corresponding flood discharge tidal rise receiving position information, where tidal rise receiving capability is usually reflected by the average tidal rise flow of the cross section, and flood discharge capability is usually reflected by the average tidal fall flow through the cross section; the average flood rising flow data, the average tide falling flow data and the corresponding flood discharge and tide receiving position information are calculated through the unit width flow to generate a sensitive river reach subarea, wherein the unit width overflow of different positions under the same hydrological condition is different due to the difference of the beach trough pattern of the river channel overflow section, and the flood discharge and tide receiving capacities of different positions are also different. Therefore, projects arranged at different single wide flow positions generate different water blocking effects, namely, the single wide flow difference of different water areas causes different sensitivity degrees for flood discharge and tide reception, and the flood discharge and tide reception influence sensitive river reach can be divided into a general sensitive water area, a more sensitive water area and a sensitive water area.
In an embodiment of the present specification, step S7 specifically includes:
generating flood prevention blocking data;
adjusting the hydrodynamic model with the flow gradient change according to the flood prevention blocking data to generate a flood prevention river sensitivity distribution model;
and performing correction deduction according to the flood prevention river sensitivity distribution model and the river bed future prediction change model to generate a prediction interference future river evolution model.
The flood prevention blocking data can be a series of data information formed by artificial interference on the river, such as distribution information of a landfill river area required by construction, and the like, and the flood prevention river sensitivity distribution model and the future river bed prediction change model are used for correction and deduction to generate a prediction interference future river evolution model, so that the method has a key effect on river construction, and can train the prediction interference future river evolution model according to a construction scheme to obtain an optimal construction scheme and construction approach.
In the embodiment of the application, according to hydrological historical data and hydrological real-time basic detection data of a river channel, a river channel water surface flow velocity area distribution diagram obtained by adding real-time river channel water flow images for processing is modeled and corrected, the accuracy of a river channel water flow real-time model is improved, the actual error of follow-up river channel research is reduced, a future change trend is deduced through calculation of original data, the future change trend is interfered, the influence trend of a river channel reconstruction scheme on the future of the river channel is determined, and the construction form and the form of engineering are evaluated and decided by different river reach, so that the construction scheme and the feasibility are perfected.
Drawings
FIG. 1 is a schematic flow chart illustrating steps of a hydrodynamic analysis decision method based on flow gradient variation according to the present invention;
FIG. 2 is a flowchart illustrating a detailed implementation procedure of step S1 in FIG. 1;
FIG. 3 is a flowchart illustrating a detailed implementation of step S3 in FIG. 1;
FIG. 4 is a flowchart illustrating a detailed implementation of step S4 in FIG. 1;
FIG. 5 is a schematic diagram of the average flow rate and division of single-width flood tide according to the present invention;
FIG. 6 is a schematic view of the average flow rate and zoning for single width tide fall according to the present invention;
FIG. 7 is a schematic representation of a sensitive watershed based on mean flow rate change gradient line break values according to the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
The technical means of the patent of the present invention will be described clearly and completely with reference to the accompanying drawings, and obviously, the described embodiments are a part of the embodiments of the present invention, not all of them. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Furthermore, the drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. The functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor methods and/or microcontroller methods.
In order to achieve the above object, the present invention provides a hydrodynamic analysis decision method based on flow gradient change, comprising the following steps:
step S1: acquiring hydrologic historical data, analyzing the hydrologic historical data and generating a moving bed model;
step S2: acquiring a real-time river water flow image, and analyzing and screening the real-time river water flow image to obtain a clear river water flow framing image sequence;
and step S3: carrying out a plurality of fixed point sampling calculations on the clear river water flow frame image sequence to generate a river water flow velocity region distribution map;
and step S4: acquiring hydrological real-time basic detection data, analyzing the hydrological real-time basic detection data and a river water surface flow velocity area distribution diagram, and generating a river water flow real-time model;
step S5: performing deduction calculation according to the moving bed model and the river flow real-time model to generate a model for predicting future river bed evolution;
step S6: carrying out partition analysis on the river channel hydrodynamic force according to the moving bed model and the river channel water flow change model to generate a hydrodynamic force model with flow gradient change;
step S7: adding obstacles to a hydrodynamic model of flow gradient change and a riverbed future prediction change model for deduction to generate a prediction interference future riverway evolution model;
step S8: and generating an optimal construction and construction decision according to the prediction interference future river channel evolution model.
The hydrologic history data of the embodiment includes: the river course rivers sand content change data, the river course impact plains change data of the past year and island change data are piled up to the river course slow current of the past year, etc., carry out the analysis to hydrology historical data and obtain the moving bed model, be favorable to the audio-visual historical evolution process that obtains the riverbed, be favorable to making the analysis to the riverbed future evolution and provide data support, can obtain the riverbed density distribution and provide technical data to bridge pedestal, the construction of river course construction projects such as water conservancy dam and edge river dykes and dams is provided technical data, carry out the analysis to river course rivers image, the velocity of flow that is favorable to the analysis to obtain river course surface rivers is analyzed river surface velocity of flow and river basin undercurrent, thereby establish more accurate river course rivers real-time model, hydrology real-time basis detection data include: the method comprises the steps of generating a riverway water flow real-time model according to hydrological real-time foundation detection data and a riverway water surface flow velocity region, considering influence factors of riverway water flow from multiple aspects so as to enable the riverway water flow real-time model to be closer to actual conditions, providing more accurate and efficient data for subsequent analysis, predicting a future riverway evolution model to be used for deducing the riverway future under natural conditions to be beneficial to development and treatment of the riverway, and providing data support for predicting the interference future riverway evolution model.
In an embodiment of the present invention, referring to fig. 1, a schematic flow chart of steps of a hydrodynamic analysis decision method based on flow gradient change is shown, in which the hydrodynamic analysis decision method based on flow gradient change includes:
step S1: acquiring hydrologic historical data, analyzing the hydrologic historical data and generating a moving bed model;
in the embodiment of the invention, the acquisition of the hydrological historical data refers to recording data of local water level according to a local hydrological monitoring bureau, generally including historical water level height and flow rate data, river water flow sand content change data, historical river impact plain change data, historical river slow flow accumulation island change data and the like, or the hydrological data of the river is detected for a period of time according to construction planning on a river section to be constructed, so that hydrological data which is more practical for a construction scheme is acquired; the moving bed model refers to a model for deducing river course water flow and a river bed along with time.
Step S2: acquiring a real-time river water flow image, and analyzing and screening the real-time river water flow image to obtain a clear river water flow framing image sequence;
in the embodiment of the invention, the real-time river water flow image is shot and recorded for a long time by erecting a camera or an unmanned aerial vehicle on the water surface of the river water flow to be detected; the clear river channel water flow framing image sequence is formed by framing through river channel water surface images, a river channel water flow framing image sequence is generated, unclear river channel framing images in the river channel water flow framing image sequence are removed, clear river channel water flow framing images are obtained, the clear river channel water flow framing images are compared according to the river channel water flow framing image sequence, position entry sequencing of the clear river channel water flow framing images in the river channel water flow framing image sequence is obtained, and the distance between the clear river channel water flow framing images is recorded, so that the clear river channel water flow framing image sequence is obtained.
And step S3: carrying out a plurality of fixed point sampling calculations on the clear river water flow frame image sequence to generate a river water flow velocity region distribution map;
in the embodiment of the invention, the step of carrying out a plurality of fixed point sampling calculations on the frame image sequence of the clear river water flow refers to the step of carrying out fixed point sampling on a plurality of positions of the river water surface ripple, and comprehensively analyzing the water surface flow velocity conditions of all positions of the shot river water surface image; the river water surface flow velocity area distribution diagram is a high-speed and high-altitude diagram of the river water surface flow velocity.
And step S4: acquiring hydrological real-time basic detection data, analyzing the hydrological real-time basic detection data and a river water surface flow velocity area distribution diagram, and generating a river water flow real-time model;
in the embodiment of the invention, the hydrological real-time basic detection data refers to hydrological monitoring data of a river channel area which needs to be analyzed recently, and general data includes data which are needed by a model and used for calculation, such as river bed depth, river bed length, rainfall, flow data and the like; the analysis of the hydrological real-time basic detection data and the river water surface flow velocity area distribution diagram refers to analysis mainly based on the hydrological real-time basic detection data and correction of the river water surface flow velocity area distribution diagram as an auxiliary to generate a model; the river course water flow real-time model is a three-dimensional model of which the water flow velocity of the river course water surface and the water flow depth changes along with the time change, and can visually observe the detection result of the detection data on the river course water flow velocity.
Step S5: carrying out partition analysis on the river channel hydrodynamic force according to the moving bed model and the river channel water flow change model to generate a hydrodynamic force model with flow gradient change;
in the embodiment of the invention, the partition analysis of the riverway water power according to the moving bed model and the riverway water flow change model means that the river water flow change model is combined with the moving bed model to carry out deduction and analysis, and the riverway water flow is partitioned into a general sensitive area, a more sensitive area and a sensitive area by taking the single wide rising and falling tide average flow change gradient mutation value as a boundary line; the hydrodynamic model of flow gradient change refers to a model combining a hydrokinetic relationship model of water flow and riverbed change and a water area division sensitive area;
wherein, the average flow value of single wide rising (falling) tide is introduced as a power partition judgment index; hydrokinetic factors mainly comprise water level, flow velocity, flow, sand content and the like, tidal power of a section of a river channel or a sea mouth is usually reflected by the average flow of rising tide of the section, and flood discharge capacity is usually reflected by the average flow of falling tide of the section; the river channel overflowing sections have different unit width overflowing amounts at different positions under the same hydrological condition due to the difference of the beach tank patterns, and have different flood discharge and tide receiving capacities at different positions; therefore, projects arranged at different single wide flow positions generate different water blocking effects, namely, the single wide flow difference of different water areas causes different sensitivity degrees for flood discharge and tide reception, and the flood discharge and tide reception influence sensitive river reach can be divided into a general sensitive water area, a more sensitive water area and a sensitive water area.
Step S6: performing deduction calculation according to the moving bed model and the river flow real-time model to generate a model for predicting future river bed evolution;
in the embodiment of the invention, the deduction calculation according to the moving bed model and the real-time river water flow model refers to deduction according to the moving bed model and the river water flow change model, and combination is performed based on a time relationship; the model for predicting the future riverbed evolution is a model which is derived and evolved according to the previous data and the change trend of the model.
Step S7: adding obstacles to a hydrodynamic model of flow gradient change and a riverbed future prediction change model for deduction to generate a prediction interference future riverway evolution model;
in the embodiment of the invention, the deduction of the adding obstruction of the hydrodynamic model of flow gradient change and the future prediction change model of the riverbed refers to the deduction of the future prediction change model of the riverbed and the hydrodynamic model of flow gradient change by adding an interference condition and combining a deduction result model of a new city; the model for predicting the future river course evolution interference refers to a model for deducing the future interference change trend by combining the external data interference condition and the internal custom-trained interference condition.
Step S8: generating an optimal construction and construction decision according to a prediction interference future river evolution model;
in the embodiment of the invention, the generation of the optimal construction and construction decision according to the prediction interference future river course evolution model refers to directly adding an interference item to the prediction interference future river course evolution model or adding the interference item through a training set of training according to engineering construction requirements, deducing through the interference item to generate a corresponding prediction interference future river course evolution model, outputting an execution result and a process of the model entry interference item, obtaining an optimal construction path through the interference item, and making a decision on the construction path and the scheme.
In one embodiment of the present specification, the hydrologic history data includes: the method comprises the following steps of 1, acquiring historical water level height and flow rate data, historical river water flow sand content change data, historical river impact plateau change data and historical river slow flow accumulation island change data, wherein the step S1 comprises the following steps:
acquiring hydrological historical data;
summarizing and analyzing the change data of the river channel impact plains and the change data of the river channel slow-flow accumulation islands in the past years to obtain the current river channel sand accumulation distribution area and distribution density;
the current river channel sand accumulation distribution area and distribution density are speculatively analyzed according to the water level height and flow speed data of the past year to generate a riverbed sediment accumulation change model;
calculating and analyzing the water level height and flow rate data in the past year to obtain a relation function of the water level height and the flow rate, and performing summary modeling on the relation function of the water level height and the flow rate and the river water sand content change data to generate a river water change model;
and aggregating the riverbed sediment accumulation change model and the riverway water flow change model to generate a moving bed model.
In the embodiment, by summarizing and analyzing the change data of the river channel impact plains in the past and the change data of the river channel slow-flow accumulation islands in the past, the accumulation distribution area and the distribution density of sand and soil in the river channel can be visually obtained, in other words, a distribution map of the sediment thickness of the river channel and a distribution map along with historical changes can be obtained, the structure and the density of a river bed can be favorably known, and the data support is improved for river channel engineering such as bridges and the like; the current river channel sand accumulation distribution area and distribution density are speculatively analyzed according to the water level height and flow velocity data of the past year to obtain a riverbed sediment accumulation change model, and the historical change of the riverbed is favorably known through analyzing the water level height and flow velocity data of the past year; calculating and analyzing the water level height and flow velocity data of the past year to obtain a relation function of the water level height and the flow velocity, summarizing and modeling the relation function of the water level height and the flow velocity and the river water sand content change data to obtain a river water flow change model, and deducing and calculating to obtain the relation function of the water level height and the flow velocity, so that the future change of the river can be estimated; the riverbed sediment accumulation change model and the riverway water flow change model are aggregated to obtain a moving bed model, and the two models are combined to facilitate visual inspection of the whole historical transition process of the riverway and provide data support for river channel construction.
As an embodiment of the present invention, referring to fig. 2, a detailed implementation step flow diagram of step S1 in fig. 1 is described, which specifically includes:
step S21: acquiring hydrological historical data;
in the embodiment of the invention, the acquisition of the hydrological historical data refers to recording data of the local water level according to the local hydrological monitoring bureau, generally including data of the height and the flow velocity of the water level in the past year, data of the change of the sand content of the water flow in the river channel, data of the change of the impact plain of the river channel in the past year, data of the change of the slow flow accumulation island in the river channel in the past year and the like, or the hydrological data of the river channel is detected for a period of time according to the construction plan, so that the hydrological data which has more practical significance to the construction scheme is acquired.
Step S22: summarizing and analyzing the change data of the river channel impact plains and the change data of the river channel slow-flow accumulation islands in the past years to obtain the current river channel sand accumulation distribution area and distribution density;
in the embodiment of the invention, the summarizing analysis of the change data of the river channel impact plains and the change data of the river channel slow-flow accumulation islands in the past years means that the change process of the river bed of the river channel is researched to know the thickness of sediment in each area of the river bed and the firmness of each area of the river bed so as to provide a basis for the construction and construction of the river bed; the current river channel sandy soil accumulation distribution area and distribution density refer to the position and thickness of the sediment of the river channel, and are used for knowing that the river channel becomes strong, so that independent construction schemes are provided for projects constructed in different areas of the river channel, and the river channel is constructed and reformed in the aspects of not influencing the river channel tide receiving, flood discharge, navigation, ecological functions and the like.
Step S23: the current river channel sand accumulation distribution area and distribution density are speculatively analyzed according to the water level height and flow speed data of the past year to generate a riverbed sediment accumulation change model;
in the embodiment of the invention, the conjecture analysis of the current river channel sand accumulation distribution area and distribution density by the historical year water level height and flow rate data means that the accumulation of the river channel sand and the water level height and flow rate of water flow are closely related, so that the relationship between the current river channel sand accumulation distribution area and distribution density and the historical year water level height and flow rate data can be known and used for establishing a related model; the riverbed sediment accumulation change model is a three-dimensional model of the riverbed of the riverway about sediment accumulation and change of water flow, can be used for visually observing riverbed change of the riverway in the past year, and is convenient for researching the relationship of the riverbed of the riverway.
Step S24: calculating and analyzing the water level height and flow rate data in the past year to obtain a relation function of the water level height and the flow rate, and performing summary modeling on the relation function of the water level height and the flow rate and the river water sand content change data to generate a river water change model;
in the embodiment of the invention, the calculation and analysis of the water level height and the flow rate data over the years means that related functions are obtained by precisely calculating the related data; the generation of the river water flow change model refers to a model for river water flow change in time periods of different seasons and different years, and is used for understanding river water flow change and providing scientific basis for river planning and treatment.
Step S25: aggregating and summarizing the riverbed sediment accumulation change model and the riverway water flow change model to generate a moving bed model;
in the embodiment of the invention, the moving bed model refers to a model for deducing river course water flow and a river bed along with time;
according to one embodiment of the invention, the sediment erosion and deposition evolution of the river channel, particularly the plain river channel, is complex, and the river channel has longitudinal and transverse deformation. In order to fully exert the flood control, shipping and comprehensive service functions of the river channel, the river situation needs to be regulated and controlled and the river channel needs to be comprehensively renovated. The engineering measures related to flood control in the comprehensive regulation of the river channel mainly comprise bank protection, bending cutting, chinese blocking, local river reach expansion and blocking, river situation adjustment and the like. In the river regulation practice, no matter in Yangtze river, yellow river or other river channels, a movable bed model test can be adopted to research a river regulation scheme and a regulation technology. Through model test research, certain evolution processes and development trends of the key river reach in a certain space and time range and the action and influence degree of the implemented river regulation engineering measures are disclosed, and scientific basis is provided for river reach planning, design and comprehensive treatment research.
In an embodiment of the present specification, the step of performing calculation analysis on the water level height and the flow rate data in the past year to obtain a function of the water level height as a function of the flow rate, where a formula for calculating the function of the water level height as a function of the flow rate includes the following formula:
water level height variation function:
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wherein the content of the first and second substances,
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expressed as a function of the variation in the height of the water level,
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as represented by the time period variable,
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expressed as a variable over a period of time
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One of the time period variables in (a),
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expressed as a certain period of time
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The corresponding upstream water flow rate is set,
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expressed as a certain period of time
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The corresponding rainfall capacity is set as the corresponding rainfall capacity,
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expressed as a certain period of time
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The corresponding industrial and civil discharge water flow,
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expressed as a certain period of time
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The average temperature of the corresponding temperature of the sample,
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expressed as a certain period of time
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Correspondingly observing the total river water evaporation capacity of the river channel,
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expressed as a certain period of time
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The corresponding total water consumption of the local industry and agriculture to the river channel,
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an offset expressed as a function;
water flow velocity variation function:
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wherein the content of the first and second substances,
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expressed as a function of the change in the flow rate of the water,
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expressed as the length of the river channel to be observed,
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expressed as the length of the river channel to be observed
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The length of one section of the river channel in the river channel,
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expressed as a certain length of the river
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The width of the corresponding downstream river channel,
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expressed as a certain length of the river
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The width of the corresponding upstream river channel,
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expressed as a certain length of the river
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The average depth of the corresponding river bed,
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expressed as a function of the variation in the height of the water level,
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an offset expressed as a function;
the relation function calculation formula of the water level height and the flow rate is as follows:
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wherein the content of the first and second substances,
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expressed as a function of water level height and flow rate,
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indicated as a start time for starting recording of the respective items of data,
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expressed as the end time of the last recorded item of data, wherein
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As represented by the time period variable,
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indicated as the initial observation position upstream of the river,
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expressed as the observation position of the downstream end of the river channel, wherein
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Expressed as the length of the river channel to be observed,
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expressed as a function of the variation in the height of the water level,
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expressed as a function of the change in the flow rate of the water,
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respectively expressed as a constant of a function, respectively,
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expressed as an offset of a function.
The water level height variation function of the embodiment is used for calculating the variation relation of the water level height of the river channel, and measuring data of the river channel in a time period is utilized
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Performing a calculation at a current time period
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Regarding the change function of the water level height, the change function of the water level height of the river channel is calculated through all-directional data, and the influence factor on the water level height is the upstream water flow
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Rainfall and rainfall
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Industrial and civil discharge water flow
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Average temperature of
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Total river water evaporation
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The total water consumption of the river channel by local industry and agriculture
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All are factors which have certain influence on the change of the river water level height, and the influence factors of the river channel with comprehensive consideration rate enable the calculated water level height change function to more accurately correspond to the current time period
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The water level height variation relation is used for predicting the future water level height; using exponential functions
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Real-time data having a direct relation to the height of the river water level is used for enhancing the function;
the water flow velocity variation function is used for calculating the variation relation of the water flow velocity of the river channel isolated water area and is utilized at the river section needing to be detected
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The flow velocity of the river reach is calculated by all the data, the change of the flow velocity of the river channel is formed into a function by all-directional data, and the influence factor on the flow velocity of the river channel has the width of a downstream river channel
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Upstream river width
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Average riverbed depth
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And water level height variation function
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The factors have certain influence on the change of the river channel water flow velocity, and the influence factors of the river channel water flow velocity are comprehensively considered, so that the calculation of the water flow velocity change function and the precision have calculation basis on the preset future river channel water flow velocity;
the relation function calculation formula of the water level height and the flow velocity is used for calculating the relation formula of the water level height and the flow velocity of water flow, and the water level height change function is utilized
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As a function of the velocity of water flow
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Form a relation function
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For obtaining a function of water level and flow rate, using a double integral pair
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The function is calculated, which is beneficial to knowing the relation of the function.
In one embodiment of the present description, step S2 includes the steps of:
acquiring a real-time river water flow image;
framing the real-time river channel water flow image to obtain a river channel water flow framing image sequence, and performing convolution on the river channel water flow framing image sequence to obtain a clear river channel water flow framing image set;
and counting the clear river water flow frame image set according to the river water flow frame image sequence to obtain the clear river water flow frame image sequence.
In the embodiment, the real-time river channel water flow image is framed to obtain the river channel water flow framed image, which is used for identifying river channel water flow ripples, calculating the water flow velocity of the river channel water surface and providing data support for subsequently establishing a river channel water flow velocity model; and counting the clear river water flow framing image set according to the river water flow framing image sequence, so as to more clearly extract a river water flow ripple image for subsequent calculation.
In the embodiment of the invention, the convolution of the river channel water flow framing image sequence refers to that images meeting the set definition requirement are screened in the convolution operation of a user-defined convolution kernel to obtain an initial framing set, and the initial key frames meeting the set acquaintance requirement are subjected to de-duplication processing through the convolution operation to obtain the clear river channel water flow framing image; the clear river water flow framing image set is counted according to the river water flow framing image sequence, namely the clear river water flow framing images are compared according to the river water flow framing image sequence, the position entry sequence of the clear river water flow framing images in the river water flow framing image sequence is obtained, and the distance between the clear river water flow framing images is recorded so as to obtain the clear river water flow framing image sequence.
In one embodiment of the present description, step S3 includes the steps of:
step S51: extracting water surface ripple characteristic points from the clear river water flow framing images in the clear river water flow framing image sequence to obtain a water surface ripple characteristic point set of each clear river water flow framing image;
step S52: matching a water surface ripple characteristic point set of a current clear river flow framing image with a water surface ripple characteristic point set of a next clear river flow framing image in the clear river flow framing image sequence to obtain a current matching characteristic point set;
step S53: matching the clear river water flow frame image with the next clear river water flow frame image in sequence according to the method in the step S52 to obtain a full-image matching feature point set, and calculating the relative position of the full-image matching feature point set in the clear river water flow frame image to generate a matching feature point motion data set;
step S54: and labeling the clear river water flow frame images according to the matched feature point motion data set and the full-image matched feature point set to generate a river water flow velocity region distribution map.
This embodiment draws surface of water ripple characteristic point to the clear river course rivers framing image in the clear river course rivers framing image sequence, be favorable to calculating that same ripple is used for calculating single point river course rivers surface of water velocity of flow in the position of other images along with the time change, obtain river course rivers surface of water velocity of flow according to the multiple spot computing mode, calculate according to the multiple spot and obtain rivers surface of water velocity condition and generate river course surface of water velocity regional distribution diagram, the follow-up research river course rivers velocity of flow of being convenient for provides data support, be favorable to setting up and correcting the operation to river course rivers velocity of flow model.
As an embodiment of the present invention, referring to fig. 3, a flowchart illustrating a detailed implementation step of step S3 in fig. 1 specifically includes:
step S31: extracting water surface ripple characteristic points from the clear river water flow framing images in the clear river water flow framing image sequence to obtain a water surface ripple characteristic point set of each clear river water flow framing image;
in the embodiment of the invention, the extraction of the water surface ripple feature points from the clear river water flow frame images in the clear river water flow frame image sequence refers to putting the clear river water flow frame images in the clear river water flow frame image sequence into pre-training convolution to perform feature extraction, wherein the number of the feature points is generally the number obtained by the pre-training and is taken as a reference.
Step S32: matching a water surface ripple characteristic point set of a current clear river flow framing image with a water surface ripple characteristic point set of a next clear river flow framing image in the clear river flow framing image sequence to obtain a current matching characteristic point set;
in the embodiment of the invention, the current matched feature point set is corresponding feature points obtained by comparing and matching the water surface ripple feature point set of the next clear river water flow framing image of the water surface ripple feature point set.
Step S33: sequentially matching the clear river water flow frame image with the next clear river water flow frame image to obtain a full-image matching feature point set, and calculating the relative position of the full-image matching feature point set in the clear river water flow frame image to generate a matching feature point motion data set;
in the embodiment of the invention, the full-image matching feature point set sequentially matches all clear river channel water flow framing images according to the matching method in the step S32, the matching feature point motion data set is used for obtaining the time between the corresponding clear river channel water flow framing images according to the total gap image of the original river channel water flow framing image sequence, calculating the motion distance of the water surface ripples in the time, and forming the matching feature point motion data set which is used for knowing the division of the water surface water flow velocity area.
Step S34: labeling the clear river water flow frame images according to the matched feature point motion data set and the full-image matched feature point set to generate a river water flow area distribution map;
in the embodiment of the invention, the distribution map of the river surface flow velocity region refers to the distribution relation of the river surface water flow velocity in space and time.
In an embodiment of the present specification, step S4 specifically is:
acquiring hydrological real-time basic inspection data, wherein the hydrological basic hydrological data comprise riverbed depth, riverbed length, rainfall and flow data;
generating average flow speed data according to precipitation and rainfall and the flow data;
calculating the average flow velocity data according to the depth and the length of the riverbed by a riverbed flow calculation formula to generate a riverbed flow velocity data distribution set;
and correcting and adjusting the river bed flow velocity data distribution set according to the river course water flow surface velocity area distribution map to generate a river course water flow real-time model.
This embodiment generates riverbed velocity of flow data distribution set through the calculation to be used for revising the adjustment to riverbed velocity of flow data distribution set to riverway water face velocity of flow regional distribution diagram, has generated the real-time model of riverway rivers, and this model plays the directly perceived display effect of model to studying riverway historical rivers change and predicting future riverway rivers change, and the popularization work and the study of being convenient for to know riverway rivers change play the auxiliary role.
As an embodiment of the present invention, referring to fig. 4, a flowchart illustrating a detailed implementation step of step S4 in fig. 1 is provided, which specifically includes:
step S41: acquiring hydrological real-time basic inspection data, wherein the hydrological basic hydrological data comprise riverbed depth, riverbed length, rainfall and flow data;
in the embodiment of the invention, the hydrological real-time basic detection data refers to hydrological monitoring data of a river channel area which needs to be analyzed recently.
Step S42: generating average flow speed data according to precipitation rainfall and flow data;
in the embodiment of the invention, the average flow speed data refers to the average flow speed data of water flow obtained by calculating the equal distance of the river reach to be detected, wherein the average calculation of the flow speed of water flow in the region is carried out in different spaces.
Step S43: calculating the average flow speed data according to the riverbed depth and the riverbed length by a riverbed flow calculation formula to generate a riverbed flow speed data distribution set;
in the embodiment of the invention, the calculation of the average flow speed data according to the riverbed depth and the riverbed length by the riverbed flow calculation formula means that the average flow speed data is calculated according to the riverbed flow calculation formula to obtain the riverbed flow, so that a riverbed flow speed data distribution set is formed.
Step S44: correcting and adjusting the river bed flow velocity data distribution set according to the river course water flow surface velocity area distribution map to generate a river course water flow real-time model;
in the embodiment of the invention, the correction and adjustment of the riverbed flow velocity data distribution set according to the riverway water surface velocity area distribution diagram refers to the steps of comparing various data, removing abnormal data volume among the data and correcting the data; the real-time river water flow model is a three-dimensional distribution model of river water flow of a river reach to be detected in space and time.
In an embodiment of the present specification, the riverbed flow calculation formula is specifically:
Figure 735113DEST_PATH_IMAGE043
wherein the content of the first and second substances,
Figure 370494DEST_PATH_IMAGE044
expressed as the flow of the river bed,
Figure 792248DEST_PATH_IMAGE003
as indicated by the time period variable,
Figure 854882DEST_PATH_IMAGE004
expressed as a variable over a period of time
Figure 463718DEST_PATH_IMAGE003
One of the time period variables in (a),
Figure 637210DEST_PATH_IMAGE045
expressed as a certain period of time
Figure 913470DEST_PATH_IMAGE004
The corresponding water flow velocity change function is adopted,
Figure 881426DEST_PATH_IMAGE040
expressed as the average bed depth of the river to be observed,
Figure 243138DEST_PATH_IMAGE038
expressed as the downstream channel width of the channel to be observed,
Figure 220321DEST_PATH_IMAGE039
expressed as the upstream channel width of the channel to be observed,
Figure 616667DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 755525DEST_PATH_IMAGE014
expressed as the length of the river channel to be observed,
Figure 338953DEST_PATH_IMAGE046
expressed as an offset of a function.
The river bed flow calculation formula is used for calculating the river flow, and measuring data of the river in a time period are utilized
Figure 119827DEST_PATH_IMAGE003
Performing a calculation at a current time period
Figure 105100DEST_PATH_IMAGE003
Regarding the water flow, the river water flow is calculated through omnibearing data, and the influence factor on the water flow has a water flow velocity change function
Figure 946017DEST_PATH_IMAGE013
Average depth of riverbed
Figure 751162DEST_PATH_IMAGE040
Downstream river width
Figure 70148DEST_PATH_IMAGE038
Upstream river width
Figure 175507DEST_PATH_IMAGE039
Water level height variation function
Figure 656167DEST_PATH_IMAGE002
And the length of the river channel to be observed
Figure 479767DEST_PATH_IMAGE014
All are factors which have certain influence on the change of the river flow, and the influence factors of the river channel with comprehensive consideration rate enable the calculated river bed flow to correspond to the current time period more accurately
Figure 336864DEST_PATH_IMAGE003
The water level height change relation is used for estimating the future river channel water flow and river channel tide receiving and flood discharging, and navigation and ecological functions of the river channel are ensured.
In an embodiment of the present specification, step S5 specifically includes:
generating real-time river channel change data through a river channel water flow real-time model and a river channel water flow self-change function calculation formula;
modifying and adjusting the moving bed model according to the real-time change data of the river channel to generate a model for predicting the future river bed evolution;
the riverway water flow self-changing function calculation formula is specifically as follows:
Figure 296730DEST_PATH_IMAGE047
wherein, the first and the second end of the pipe are connected with each other,
Figure 213871DEST_PATH_IMAGE048
the river course water flow is self-changing function,
Figure 259187DEST_PATH_IMAGE023
indicated as the end time of the last recording of each item of data,
Figure 654396DEST_PATH_IMAGE014
expressed as the length of the river channel to be observed,
Figure 734348DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed
Figure 822389DEST_PATH_IMAGE014
The length of one section of the river channel in the river channel,
Figure 355002DEST_PATH_IMAGE021
expressed as a function of water level height and flow rate,
Figure 819481DEST_PATH_IMAGE049
expressed as the sand content of the river channel per unit time,
Figure 753939DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 747303DEST_PATH_IMAGE013
representAs a function of the change in the flow rate of the water stream,
Figure 767212DEST_PATH_IMAGE044
expressed as the flow of the river bed,
Figure 35382DEST_PATH_IMAGE050
expressed as an offset of a function.
The river course water flow self-changing function calculation formula is used for calculating the river course water flow self-changing condition, and measuring data of the river course in a time period is utilized
Figure 824346DEST_PATH_IMAGE003
Performing a calculation at a current time period
Figure 988612DEST_PATH_IMAGE003
The water flow self-change is calculated through omnibearing data, and the influence factor of the water flow self-change has a relation function of water level height and flow velocity
Figure 495816DEST_PATH_IMAGE021
And the sand content of the river channel in unit time
Figure 302098DEST_PATH_IMAGE049
Water level height variation function
Figure 679990DEST_PATH_IMAGE002
Figure 546315DEST_PATH_IMAGE028
Water flow velocity variation function and riverbed flow
Figure 275236DEST_PATH_IMAGE044
The calculation and the conjecture of the future change direction and distance of the river water flow are carried out, and the influence factor of the river channel with the overall consideration rate enables the calculation of the self-change of the river channel to be more accurate and correspond to the current time period
Figure 885209DEST_PATH_IMAGE003
Relation of water level height change ofThe influence of the relationship quantity of the historical data of each section of the river channel on the self-change of the river channel is increased through accumulation, the derivative is carried out on the influence to obtain the relationship slope and the area of the function, the relationship slope and the area are used for estimating the self-change direction and the self-change trend of the river channel, the establishment of a model for predicting the future river bed evolution is facilitated, the prediction of the future change of the river bed is facilitated, and the direction is provided for the future development and construction of the river channel.
In an embodiment of the present specification, step S6 specifically is:
performing partition analysis on riverway water power according to hydrological historical data, a moving bed model and a riverway water flow change model to generate average tidal rising flow data, average tidal falling flow data and corresponding flood discharge and tide receiving position information;
and generating a sensitive river reach subarea through unit width flow calculation according to the average rising tide flow data, the average falling tide flow data and the corresponding flood discharge tide-receiving position information, wherein the sensitive river reach subarea comprises general sensitive water area information, more sensitive water area information and sensitive water area information, and a hydrodynamic model of flow gradient change is generated.
In this embodiment, river hydrodynamic force is subjected to partition analysis according to hydrological historical data, a moving bed model and a river flow change model to generate average tidal flow rising data, average tidal flow falling data and corresponding flood discharge tidal flow receiving position information, where tidal flow receiving capability is usually reflected by tidal flow rising average flow of the section, and flood discharge capability is usually reflected by tidal flow falling average flow passing through the section; the average flood rising flow data, the average tide falling flow data and the corresponding flood discharge and tide receiving position information are calculated through the unit width flow to generate a sensitive river reach subarea, wherein the unit width overflow of different positions under the same hydrological condition is different due to the difference of the beach trough pattern of the river channel overflow section, and the flood discharge and tide receiving capacities of different positions are also different. Therefore, projects arranged at different single wide flow positions generate different water blocking effects, namely, the single wide flow difference of different water areas causes different sensitivity degrees for flood discharge and tide reception, and the flood discharge and tide reception influence sensitive river reach can be divided into a general sensitive water area, a more sensitive water area and a sensitive water area.
According to one embodiment of the invention, the Huangmao Haitai estuarine bay water area is simultaneously influenced by runoff and tide, as the water area involved in the engineering is wide, the dynamic characteristics of different areas have great difference, corresponding to the functions of flood discharge, tide collection, sand discharge and the like, the contribution of each dynamic subarea is different, for controlling the influence of the engineering on flood discharge and tide collection, the dynamic subarea must be firstly determined to optimize the overall arrangement of the wading engineering, and the hydrodynamic model with the flow gradient change is used for analysis;
and introducing the average flow value of the single wide rising (falling) tide as a power partition judgment index. The hydrohydrodynamic factors mainly comprise water level, flow speed, flow rate, sand content and the like, the tidal power of the Huangmao ocean estuary section is usually reflected by the average flow of rising tide of the section, and the flood discharge capacity is usually reflected by the average flow of falling tide through the section. The river channel overflowing section has different unit width overflowing amounts at different positions under the same hydrological condition due to the difference of the structure of the beach tank, and has different flood discharge and tide receiving capabilities at different positions. Therefore, projects arranged at different single wide flow positions generate different water blocking effects, namely, the single wide flow difference of different water areas causes different sensitivity degrees for flood discharge and tide reception, and the flood discharge and tide reception influence sensitive river reach can be divided into a general sensitive water area, a more sensitive water area and a sensitive water area;
based on the concept of single-width flow, a unit-width flow calculation formula is established: q = V × H (m 3/s). Selecting a '2001.2' dry water and big tide hydrological combination capable of reflecting the capacity of receiving tide by the Huangmao sea by utilizing a mathematical model of eight-gate tide flows at the river mouth of the Zhujiang river, calculating the average flow rate of single-width rising tide at the river mouth of the Zhujiang river, drawing a distribution diagram of the average flow rate of single-width rising tide at the river mouth of the Huangmao sea, as shown in a figure 5, selecting a '2005.6' flood and big tide hydrological combination capable of reflecting the capacity of discharging flood at the river mouth of the Zhujiang river, and calculating the average flow rate of single-width falling tide at the river mouth of the Zhujiang river, as shown in a figure 6;
the sensitive water area of the estuary adopts a single wide swelling and falling tide average flow change gradient mutation value as a boundary, and can be divided into a general sensitive area, a more sensitive area and a sensitive area, wherein the sensitive area is mainly distributed in a deep groove area of a citronella sea estuary, the more sensitive area is mainly distributed in a middle deeper area, and the general sensitive area is mainly distributed in shallow beach areas at the east and west sides and is used for forming a hydrodynamic model of flow gradient change;
(1) And (3) dividing a moisture channel sensitive area:
referring to FIG. 5, there is shown a single wide flood tide average flow and zoning scheme of the present invention, wherein the numbers in the figure are
Figure DEST_PATH_IMAGE051
The corresponding area is in corresponding relation with the unit tidal volume value on the right side, and the original unit tidal volume value is corresponding to the area with different colors marked with serial numbers;
the single-width tide rising average flow distribution diagram under the condition of combination of '2001.2' and the water and features clearly showing the tide receiving tasks borne by different beach trough water areas of the Huangmao sea, wherein the flood discharging and tide receiving tasks in the deep trough area of the middle east side where the deep yellow color is located are most prominent, and the tide receiving tasks in the light yellow beach areas of the two sides, particularly the near-shore beach area of the west side, are smaller.
(2) Dividing a sensitive area of a flood discharge channel:
referring to FIG. 6, a single width tide fall average flow and zone diagram according to the present invention is shown, wherein the numbers in the diagram are numbered
Figure 383187DEST_PATH_IMAGE052
The corresponding area is in corresponding relation with the unit tidal volume value on the right side, and the original unit tidal volume value is corresponding to the area with different colors marked with serial numbers;
the single-width tide falling average flow distribution diagram under the flood and large tide hydrologic combination condition of 2005.6 can clearly show the flood discharge tasks borne by different beach groove water areas of the Huangmao sea, wherein the flood discharge tasks of the red channel and the deep grooves on the two sides are the most prominent, and the flood discharge tasks of the shallow areas on the east and west sides are smaller.
By combining the flood discharge and tidal volume receiving analysis, the runoff power main control area mainly comprising deep water areas with the channel and the contour lines of-5 m at two sides and the tidal power main control area mainly comprising the middle east part exist in the Huangmao estuary, after scalar quantity superposition is carried out on the two figures, the water areas between-4 m and-5 m also belong to sensitive water areas, and the flood discharge and tidal volume receiving sensitive area of the Huangmao estuary can be obtained as shown in fig. 7. And drawing a horizontal single-width expansion and falling tide average flow change gradient line of the estuary according to the single-width expansion and falling tide average comprehensive flow distribution diagram, and connecting the single-width expansion and falling tide average flow change gradient values along the longitudinal direction. The method comprises the steps that sudden change values of obvious change gradient lines exist on two sides of a navigation channel and the edge of a shoal, and flood discharge and tide receiving flow sudden change areas can be accurately distinguished according to the boundary line, so that the sudden change values of the single-width fluctuation tide average flow change gradient lines are selected as standards of a general sensitive area, a sensitive area and a sensitive area, and partitions of sensitive water areas influenced by flood discharge and tide receiving are drawn so as to be used for constructing a hydrodynamic model of flow gradient change of a local sea entrance;
referring to FIG. 7, a schematic diagram of a sensitive water subarea based on the abrupt change value of the mean flow rate change gradient line according to the present invention is shown, wherein the numbers in the diagram are indicated
Figure DEST_PATH_IMAGE053
The corresponding area corresponds to the unit tidal volume value on the right side.
In an embodiment of the present specification, step S7 specifically includes:
generating flood prevention blocking data;
adjusting the hydrodynamic model with the flow gradient change according to the flood prevention blocking data to generate a flood prevention river sensitivity distribution model;
and performing correction deduction according to the flood prevention river sensitivity distribution model and the river bed future prediction change model to generate a prediction interference future river evolution model.
The flood prevention blocking data can be a series of data information formed by artificial interference on the river, such as distribution information of a landfill river area required by construction, and the like, and the flood prevention river sensitivity distribution model and the future river bed prediction change model are used for correction and deduction to generate a prediction interference future river evolution model, so that the method has a key effect on river construction, and can train the prediction interference future river evolution model according to a construction scheme to obtain an optimal construction scheme and construction approach.
In the embodiment of the invention, the flood prevention blocking data refers to interference data obtained by directly adding an interference item to a prediction interference future river channel evolution model or adding an interference item through a training set of training according to engineering construction requirements, the adjustment of the hydrodynamic model with flow gradient change according to the flood prevention blocking data refers to deduction and adjustment of the hydrodynamic model with flow gradient change through the interference item, and the correction and deduction according to the flood prevention river channel sensitivity distribution model and a river bed future prediction change model refers to deduction and generation of a corresponding prediction interference future river channel evolution model through the interference item.
As an embodiment of the invention, river shoreline development and utilization mainly include bank protection, river-crossing bridges, tunnels, water intakes, water outlets, ports and docks, river-crossing submarine cables, and the like; in the process of river channel development and utilization, the technical means of predicting and interfering future river channel evolution model tests can be adopted to research the water flow characteristics and sediment scouring characteristics of the planned engineering river reach before and after the engineering and the influence of the planned engineering on flood control, river situation and navigation channels, and simultaneously, the shore line resource utilization and engineering design scheme is optimized according to the model test result, and corresponding improvement and reduction measures are provided for adverse effects in the process of river channel development and utilization.
As an embodiment of the invention, the model for predicting and interfering future river evolution plays a role in the fields of traditional river development and utilization, and also plays a role in ecological and environmental problem related experimental research such as river concentration fields, temperature fields, pollutant diffusion prevention, oncomelania diffusion prevention, river ecological restoration engineering and the like, and the research results can be applied to scientific research, planning, engineering design and decision management.
As an embodiment of the invention, the natural conditions of the newly built and built deep-water channels and ports are complex, wherein the problem of silt is a great problem which must be solved; although the movement of water and sand of the estuary coast is more complex than that of a river channel, the key of the research problem of grasping a river channel evolution model in the future can be used for predicting interference, a conclusion which is closer to the reality than a mathematical model can be obtained, a basis is provided for the research and the solution of the estuary coast problem, and a great effect is played on the development of the estuary coast subject.
According to the method and the device, a river water flow velocity area distribution diagram obtained by adding real-time river water flow images for processing is modeled and corrected according to hydrological historical data and hydrological real-time basic detection data of a river, the accuracy of a river water flow real-time model is improved, actual errors of follow-up river research are reduced, a future change trend is deduced through calculation of original data, the future change trend is interfered, the influence trend of a river channel reconstruction scheme on the future river is determined, and the construction form and the form of engineering in different river reach are evaluated and decided, so that the construction scheme and the feasibility are improved.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A hydrodynamic analysis decision method based on flow gradient changes, the method comprising the steps of:
step S1: acquiring hydrologic historical data, analyzing the hydrologic historical data and generating a moving bed model;
step S2: acquiring a real-time river water flow image, and analyzing and screening the real-time river water flow image to obtain a clear river water flow framing image sequence;
and step S3: carrying out a plurality of fixed point sampling calculations on the clear river water flow frame image sequence to generate a river water flow velocity region distribution map;
and step S4: acquiring hydrological real-time basic detection data, analyzing the hydrological real-time basic detection data and a river water surface flow velocity area distribution diagram, and generating a river water flow real-time model;
step S5: performing deduction calculation according to the moving bed model and the river flow real-time model to generate a model for predicting future river bed evolution;
step S6: carrying out partition analysis on the river channel hydrodynamic force according to the moving bed model and the river channel water flow change model to generate a hydrodynamic force model with flow gradient change;
step S7: adding obstacles into a hydrodynamic model of flow gradient change and a riverbed future prediction change model for deduction to generate a prediction interference future riverway evolution model;
step S8: and generating an optimal construction and construction decision according to the prediction interference future river evolution model.
2. The method of claim 1, wherein the hydrologic history data comprises: the method comprises the following steps of 1, acquiring historical water level height and flow rate data, historical river water flow sand content change data, historical river impact plateau change data and historical river slow flow accumulation island change data, wherein the step S1 comprises the following steps:
acquiring hydrological historical data;
summarizing and analyzing the change data of the river channel impact plains and the change data of the river channel slow-flow accumulation islands in the past years to obtain the current river channel sand accumulation distribution area and distribution density;
the current river channel sand accumulation distribution area and distribution density are speculatively analyzed according to the water level height and flow speed data of the past year to generate a riverbed sediment accumulation change model;
calculating and analyzing the water level height and flow rate data in the past year to obtain a relation function of the water level height and the flow rate, and performing summary modeling on the relation function of the water level height and the flow rate and the river water sand content change data to generate a river water change model;
and aggregating the riverbed sediment accumulation change model and the riverway water flow change model to generate a moving bed model.
3. The method of claim 2, wherein the historical water level and flow rate data is computationally analyzed to obtain a function of water level and flow rate, wherein the formula for calculating the function of water level and flow rate from the historical water level and flow rate data comprises the following formula:
water level height variation function:
Figure DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 109735DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure DEST_PATH_IMAGE003
as represented by the time period variable,
Figure 745116DEST_PATH_IMAGE004
expressed as a variable over a period of time
Figure 166870DEST_PATH_IMAGE003
One of the time period variables in (a),
Figure DEST_PATH_IMAGE005
expressed as a certain period of time
Figure 229504DEST_PATH_IMAGE004
The flow rate of the corresponding upstream water flow,
Figure 103919DEST_PATH_IMAGE006
expressed as a certain period of time
Figure 11832DEST_PATH_IMAGE004
The corresponding rainfall capacity is set as the corresponding rainfall capacity,
Figure DEST_PATH_IMAGE007
expressed as a certain period of time
Figure 553672DEST_PATH_IMAGE008
The corresponding industrial and civil discharge water flow,
Figure DEST_PATH_IMAGE009
expressed as a certain period of time
Figure 787207DEST_PATH_IMAGE004
The average temperature of the corresponding temperature of the sample,
Figure 148918DEST_PATH_IMAGE010
expressed as a certain period of time
Figure 126102DEST_PATH_IMAGE004
Correspondingly observing the total river water evaporation capacity of the river channel,
Figure DEST_PATH_IMAGE011
expressed as a certain period of time
Figure 256869DEST_PATH_IMAGE004
The corresponding total water consumption of the local industry and agriculture to the river channel,
Figure 661305DEST_PATH_IMAGE012
an offset expressed as a function;
water flow velocity variation function:
Figure DEST_PATH_IMAGE013
wherein the content of the first and second substances,
Figure 510313DEST_PATH_IMAGE014
expressed as a function of the change in the flow rate of the water,
Figure 291187DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed,
Figure DEST_PATH_IMAGE016
expressed as the length of the river channel to be observed
Figure 276460DEST_PATH_IMAGE015
The length of one section of the river channel in the river channel,
Figure 851798DEST_PATH_IMAGE017
expressed as a certain length of the river
Figure 188102DEST_PATH_IMAGE016
The width of the corresponding downstream river channel,
Figure DEST_PATH_IMAGE018
expressed as a certain length of the river
Figure 507087DEST_PATH_IMAGE016
Corresponding upstreamThe width of the river channel is controlled by the control system,
Figure 612447DEST_PATH_IMAGE019
expressed as a certain length of the river
Figure 93107DEST_PATH_IMAGE016
The average depth of the corresponding river bed,
Figure 916706DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure DEST_PATH_IMAGE020
an offset expressed as a function;
the relation function calculation formula of the water level height and the flow rate is as follows:
Figure 773804DEST_PATH_IMAGE021
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE022
expressed as a function of water level height and flow rate,
Figure 999249DEST_PATH_IMAGE023
indicated as a start time for starting recording of the respective items of data,
Figure DEST_PATH_IMAGE024
expressed as the end time of the last recorded item of data, wherein
Figure 181968DEST_PATH_IMAGE025
Figure 227285DEST_PATH_IMAGE003
As indicated by the time period variable,
Figure DEST_PATH_IMAGE026
indicated as the initial observation position upstream of the river,
Figure 888073DEST_PATH_IMAGE027
expressed as the observation position of the downstream end of the river channel, wherein
Figure DEST_PATH_IMAGE028
Figure 968025DEST_PATH_IMAGE015
Expressed as the length of the river channel to be observed,
Figure 56066DEST_PATH_IMAGE002
expressed as a function of the variation in the height of the water level,
Figure 588679DEST_PATH_IMAGE014
expressed as a function of the change in the flow rate of the water,
Figure 53158DEST_PATH_IMAGE029
respectively, are represented as constants of a function,
Figure DEST_PATH_IMAGE030
expressed as an offset of a function.
4. The method according to claim 1, characterized in that step S2 comprises the steps of:
acquiring a real-time river water flow image;
framing the real-time river channel water flow image to obtain a river channel water flow framing image sequence, and performing convolution on the river channel water flow framing image sequence to obtain a clear river channel water flow framing image set;
and counting the clear river water flow frame image set according to the river water flow frame image sequence to obtain the clear river water flow frame image sequence.
5. The method according to claim 1, characterized in that step S3 comprises the steps of:
step S51: extracting water surface ripple characteristic points from the clear river water flow framing images in the clear river water flow framing image sequence to obtain a water surface ripple characteristic point set of each clear river water flow framing image;
step S52: matching a water surface ripple characteristic point set of a current clear river flow framing image with a water surface ripple characteristic point set of a next clear river flow framing image in a clear river flow framing image sequence to obtain a first matching characteristic point set;
step S53: matching the clear river water flow frame image with the next clear river water flow frame image in sequence according to the method in the step S52 to obtain a full-image matching feature point set, and calculating the relative position of the full-image matching feature point set in the clear river water flow frame image to generate a matching feature point motion data set;
step S54: and labeling the clear river water flow frame images according to the matched feature point motion data set and the full-image matched feature point set to generate a river water flow velocity region distribution map.
6. The method according to claim 1, wherein step S4 is specifically:
acquiring hydrological real-time basic inspection data, wherein the hydrological basic hydrological data comprise riverbed depth, riverbed length, rainfall and flow data;
generating average flow speed data according to precipitation and rainfall and the flow data;
calculating the average flow speed data according to the riverbed depth and the riverbed length by a riverbed flow calculation formula to generate a riverbed flow speed data distribution set;
and correcting and adjusting the river bed flow velocity data distribution set according to the river channel water surface flow velocity region distribution map to generate a river channel water flow real-time model.
7. The method according to claim 6, wherein the riverbed flow calculation formula is specifically:
Figure 987616DEST_PATH_IMAGE031
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE032
expressed as the flow of the river bed,
Figure 246559DEST_PATH_IMAGE033
as represented by the time period variable,
Figure 266468DEST_PATH_IMAGE004
expressed as a variable over a period of time
Figure 3480DEST_PATH_IMAGE033
One of the time period variables in (a),
Figure DEST_PATH_IMAGE034
expressed as a certain period of time
Figure 58023DEST_PATH_IMAGE004
The corresponding water flow velocity change function,
Figure 487868DEST_PATH_IMAGE035
expressed as the average bed depth of the river to be observed,
Figure DEST_PATH_IMAGE036
expressed as the downstream channel width of the channel to be observed,
Figure 260652DEST_PATH_IMAGE037
expressed as the upstream channel width of the channel to be observed,
Figure DEST_PATH_IMAGE038
expressed as a function of the variation in the height of the water level,
Figure 801354DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed,
Figure 722123DEST_PATH_IMAGE039
expressed as an offset of a function.
8. The method according to claim 1, wherein step S5 is specifically:
generating real-time river channel change data through a river channel water flow real-time model and a river channel water flow self-change function calculation formula;
modifying and adjusting the moving bed model according to real-time river channel change data to generate a model for predicting future river bed evolution;
the riverway water flow self-changing function calculation formula is specifically as follows:
Figure DEST_PATH_IMAGE040
wherein the content of the first and second substances,
Figure 322869DEST_PATH_IMAGE041
the river course water flow is self-changing function,
Figure DEST_PATH_IMAGE042
indicated as the end time of the last recording of each item of data,
Figure 317370DEST_PATH_IMAGE015
expressed as the length of the river channel to be observed,
Figure 661763DEST_PATH_IMAGE016
expressed as the length of the river channel to be observed
Figure 425320DEST_PATH_IMAGE015
The length of one section of the river channel in the river channel,
Figure 196967DEST_PATH_IMAGE043
expressed as a function of water level height and flow rate,
Figure DEST_PATH_IMAGE044
expressed as the sand content of the river channel per unit time,
Figure 678764DEST_PATH_IMAGE038
expressed as a function of the variation in the height of the water level,
Figure 826849DEST_PATH_IMAGE045
expressed as a function of the change in the flow rate of the water,
Figure 179332DEST_PATH_IMAGE032
expressed as the flow of the river bed,
Figure DEST_PATH_IMAGE046
expressed as an offset of a function.
9. The method according to claim 1, wherein step S6 is specifically:
performing partition analysis on riverway water power according to hydrological historical data, a moving bed model and a riverway water flow change model to generate average tidal rising flow data, average tidal falling flow data and corresponding flood discharge and tide receiving position information;
and generating a sensitive river reach subarea by unit width flow calculation according to the average rising flow data, the average falling flow data and the corresponding flood discharge and tide receiving position information, wherein the sensitive river reach subarea comprises general sensitive water area information, more sensitive water area information and sensitive water area information, and a hydrodynamic model with flow gradient change is generated.
10. The method according to claim 1, wherein step S7 is specifically:
generating flood prevention blocking data;
adjusting the hydrodynamic model with the flow gradient change according to the flood prevention blocking data to generate a flood prevention river sensitivity distribution model;
and performing correction deduction according to the flood prevention river sensitivity distribution model and the river bed future prediction change model to generate a prediction interference future river evolution model.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116227390A (en) * 2023-05-09 2023-06-06 珠江水利委员会珠江水利科学研究院 River water environment remediation and water ecological remediation method and system
CN116309555A (en) * 2023-05-15 2023-06-23 中国船舶集团有限公司第七〇七研究所 Integrated circuit feature extraction method based on multi-physical quantity fusion
CN116522446A (en) * 2023-04-28 2023-08-01 珠江水利委员会珠江水利科学研究院 Method for defining main channel of estuary bay tidal current sediment

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102383394A (en) * 2011-08-09 2012-03-21 黄河水利委员会黄河水利科学研究院 Test method of rive project movable bed physical model coupling
US20170292839A1 (en) * 2016-04-11 2017-10-12 National Applied Research Laboratories Composite hydrological monitoring system
CN108532532A (en) * 2018-04-12 2018-09-14 福建省水利水电勘测设计研究院 The moisture-proof water front formulating method of tidal waterway flood control
CN113585161A (en) * 2021-08-17 2021-11-02 扬州大学 Construction method of alluvial river deep body lateral migration prediction model
CN114218840A (en) * 2021-12-27 2022-03-22 河海大学 Integral modeling and visualization system for river mouth channel water and sand movement and terrain evolution thereof
CN115293062A (en) * 2022-07-13 2022-11-04 武汉大学 Method and equipment for analyzing stage of riverbed evolution
CN115293037A (en) * 2022-08-03 2022-11-04 武汉大学 Hydrodynamic modeling method of river and lake composite system based on machine learning

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102383394A (en) * 2011-08-09 2012-03-21 黄河水利委员会黄河水利科学研究院 Test method of rive project movable bed physical model coupling
US20170292839A1 (en) * 2016-04-11 2017-10-12 National Applied Research Laboratories Composite hydrological monitoring system
CN108532532A (en) * 2018-04-12 2018-09-14 福建省水利水电勘测设计研究院 The moisture-proof water front formulating method of tidal waterway flood control
CN113585161A (en) * 2021-08-17 2021-11-02 扬州大学 Construction method of alluvial river deep body lateral migration prediction model
CN114218840A (en) * 2021-12-27 2022-03-22 河海大学 Integral modeling and visualization system for river mouth channel water and sand movement and terrain evolution thereof
CN115293062A (en) * 2022-07-13 2022-11-04 武汉大学 Method and equipment for analyzing stage of riverbed evolution
CN115293037A (en) * 2022-08-03 2022-11-04 武汉大学 Hydrodynamic modeling method of river and lake composite system based on machine learning

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
XIANG-YANG TU 等: "Study on the hydrodynamic", 《2ND INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING, ANDINTELLIGENT COMPUTING, 2022》 *
YUNWEN PAN 等: "Effects of discharge on the velocity distribution and riverbed evolution in a meandering channel", 《JOURNAL OF HYDROLOGY》 *
刘国珍 等: "茅洲河口滩槽自生性物理模型试验研究", 《中国农村水利水电》 *
叶丽清等: "闽江下游闽清河段河道演变分析", 《水利与建筑工程学报》 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116522446A (en) * 2023-04-28 2023-08-01 珠江水利委员会珠江水利科学研究院 Method for defining main channel of estuary bay tidal current sediment
CN116522446B (en) * 2023-04-28 2023-12-05 珠江水利委员会珠江水利科学研究院 Method for defining main channel of estuary bay tidal current sediment
CN116227390A (en) * 2023-05-09 2023-06-06 珠江水利委员会珠江水利科学研究院 River water environment remediation and water ecological remediation method and system
CN116227390B (en) * 2023-05-09 2023-07-07 珠江水利委员会珠江水利科学研究院 River water environment remediation and water ecological remediation method and system
CN116309555A (en) * 2023-05-15 2023-06-23 中国船舶集团有限公司第七〇七研究所 Integrated circuit feature extraction method based on multi-physical quantity fusion
CN116309555B (en) * 2023-05-15 2023-07-25 中国船舶集团有限公司第七〇七研究所 Integrated circuit feature extraction method based on multi-physical quantity fusion

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